psfm: psfm

In davidhbernstein/sfm: Stochastic Frontier Models

psfm

Description

Main panel function of package

Usage

psfm(formula, model_name = c("TRE_Z", "GTRE_Z", "TRE", "GTRE", "WMLE", "FD", "GTRE_SEQ1", "GTRE_SEQ2"), data, maxit.bobyqa = 100, maxit.psoptim = 10, maxit.optim = 10, REPORT = 1, trace = 3, pgtol = 0, individual, halton_num = NULL, start_val = FALSE, gamma = FALSE, PSopt = FALSE, bob = TRUE, optHessian = TRUE, inefdec = TRUE, Method = "L-BFGS-B")

Arguments

formula	a symbolic description for the model to be estimated
model_name	model name for the estimation
data	a pdata.frame
maxit.bobyqa	Maximum number of iterations for the bobyqa optimization routine
maxit.psoptim	Maximum number of iterations for the psoptim optimization routine
maxit.optim	Maximum number of iterations for the optim optimization routine
REPORT	reporting parameter
trace	trace
pgtol	pgtol
individual	individual unit in the regression model
halton_num	number of Halton draws to use in SML models
start_val	starting value (optional)
gamma	gamma
PSopt	use psoptim optimization routine (T/F)
bob	use bobyqa optimization routine (T/F)
optHessian	Logical. Should a numerically differentiated Hessian matrix be returned? (for optim routine)
inefdec	Production or cost function
Method	The method to be used for optim. See ‘Details’ within optim.

Note

The generalized true random effects model (GTRE, 4-component model) and true random effects models (TRE) are both estimated by simulated maximum likelihood based on the paper by the Fillipini and Greene (2016, JPA). The TRE_Z and GTRE_Z allow for modeling the u-component of the GTRE and TRE with determinants of inefficiency. The first-difference model (FD) of Wang and Ho (2010, JoE) as well as the within-maximum likelihood (WMLE) of Chen, Schmidt and Wang (2014, JoE) are also available.

Author(s)

David Bernstein

References

Fillipini and Greene (2016, JPA); Wang and Ho (2010, JoE); Chen, Schmidt and Wang (2014, JoE)

See Also

NA

Examples

data_trial <- data_gen_p(t=10,N=100, rand = 100, 
                         sig_u = 1,  sig_v = 0.3, 
                         sig_r = .2, sig_h = .4, 
                         cons = 0.5, beta1 = 0.5,
                         beta2 = 0.5)
## Trial runs:
max_fd          <-   psfm(formula = y_fd ~  x_fd|z_fd,
                          model_name = "FD",  
                          data=data_trial, 
                          individual = "name")

max_tre_z   <-  psfm(formula    = y_tre_z ~ x1 +x2| z_gtre, 
                     model_name = "TRE",                    ## "TRE_Z" also works
                     data       = p.data,
                     individual = "name",
                     PSopt      = TRUE)

max_gtre         <-   psfm(formula = y_gtre ~ x1+x2,    
                           model_name = "GTRE", 
                           data=data_trial,
                           individual = "name")

max_tre    <-   psfm(formula = y_tre ~  x1+x2,    
                     model_name = "TRE",  
                     data=data_trial, 
                     individual = "name")

max_wmle   <-   psfm(formula = y_wmle~ x1_w + x2_w,
                     model_name = "WMLE",
                     data=data_trial,
                     individual = "name")

davidhbernstein/sfm documentation built on Feb. 28, 2025, 1:17 a.m.